时间：2020-11-27 10:44:03 | 栏目：Python代码 | 点击：次
第一种：使用extend()
>>> lines = open('test.txt').readlines()
>>> lines
['1\n', '2\n', '3\n', '4,5\n']
>>> for line in lines:
... ll.extend(line.strip().split(','))
...
>>> ll
['1', '2', '3', '4', '5']
第二种：使用+
>>> ll = []
>>> lines = open('test.txt').readlines()
>>> lines
['1\n', '2\n', '3\n', '4,5\n']
>>> for line in lines:
... ll = ll + line.strip().split(',')
...
>>> ll
['1', '2', '3', '4', '5']
第三种：使用flat array数组的自带方法
>>> ll = []
>>> lines = open('test.txt').readlines()
>>> for line in lines:
... ll.append(line.strip().split(','))
...
>>> ll = np.array(ll)
>>> np.hstack(ll.flat)
array(['1', '2', '3', '4', '5'],
dtype='|S1')
>>> list(np.hstack(ll.flat))
['1', '2', '3', '4', '5']
总结：
1. extend()与append()的区别
append()可以接受任何数据类型和格式的数据作为一个元素插入原list
extend() 则仅能将任何数据类型和格式的数据展开作为一组元素插入原list
eg.
>>> a = [1,'a'] >>> a.extend(np.array([2,'b'])) >>> a [1, 'a', '2', 'b'] >>> a.extend([3,['c']]) >>> a [1, 'a', '2', 'b', 3, ['c']] >>> a = [1,'a'] >>> a.extend(np.array([2,'b'])) >>> a [1, 'a', '2', 'b'] >>> a.extend([3,['c']]) >>> a [1, 'a', '2', 'b', 3, ['c']] >>> a = [1,'a'] >>> a.append(np.array([2,'b'])) >>> a [1, 'a', array(['2', 'b'], dtype='|S21')] >>> a.append([3,['c']]) >>> a [1, 'a', array(['2', 'b'], dtype='|S21'), [3, ['c']]]
2. flatten()无法对dtype = object的array进行展开，dtype = object说明array中的元素是list，即其不是满矩阵结构
eg.
>>> a = np.array([[1,2],[3,4]])
>>> a.dtype
dtype('int64')
>>> a.flatten()
array([1, 2, 3, 4])
>>>
>>> a = np.array([[1,2],[3,4],[5]])
>>> a.flatten()
array([[1, 2], [3, 4], [5]], dtype=object)
3.readlines读取文件默认str，可以通过map转换数据类型
eg.
>>> ll = []
>>> lines = open('test.txt').readlines()
>>> lines
['1\n', '2\n', '3\n', '4,5\n']
>>> for line in lines:
... ll.append(map(int,line.strip().split(',')))
...
>>> ll
[[1], [2], [3], [4, 5]]